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Record W7056863465

Geotechnical Investigation of Subaqueous Sediment Dynamics: A Case Study from the Arctic

2016· article· en· W7056863465 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity of New Hampshire Scholars Repository (University of New Hampshire at Manchester) · 2016
Typearticle
Languageen
FieldMaterials Science
TopicHigh voltage insulation and dielectric phenomena
Canadian institutionsnot available
Fundersnot available
KeywordsSedimentPermafrostCoastal erosionSubmarine pipelineErosionAeolian processesSedimentary budgetMass wastingSeabed
DOInot available

Abstract

fetched live from OpenAlex

Subaqueous sediment dynamics including sediment erosion and deposition processes are directly related to sediment properties. In current sediment dynamics models and predictions, these sediment properties are often represented by the median grain size while other geotechnical parameters such as density, sediment strength, cohesion and pore water behavior are neglected. This results from existing uncertainties and gaps in knowledge about how geotechnical sediment characteristics change with ongoing sediment remobilization processes and vice versa. Potential consequences are uncertainties regarding the assessment of erodibility, sediment settling, consolidation and overall sediment stability. This impacts particularly current scientific, societal and engineering issues such as coastline protection and conservation, the resilience and sustainability of coastal infrastructure and communities, as well as the development of offshore and ocean renewable energy. After a brief overview of current research questions and developments, this presentation will feature results from a case study on coastal erosion in the Arctic. Herschel Island in the Yukon Territory, Canada, is located approximately 200 miles north of the polar circle, and suffers currently from permafrost retreat, some of the largest mud slumps in the world, and coastline erosion documented in the order of meters per year. In the framework of the international research expedition YUKON14 in 2014, geotechnical field tests were conducted in the nearshore zone of Herschel Island. The results indicated strong spatial heterogeneity of sediment distributions from gravelly to fine muddy sediments, vertical sediment stratification in the upper meter of the seabed surface including weak layers, and a variety of sub- and suprahydrostatic pore pressures associated to the respective stratification. This suggested a complex sediment transport and deposition pattern in the region, particularly under influence of (i) large sediment mass deposition events in response to the adjacent mud slumps and (ii) seasonal freeze-thaw cycles. Presenter Bio Nina received a Diploma (M.Sc.) in Geophysics in 2007 from the Westphalian Wilhelms University of Muenster, Germany. For her thesis, Characterization of seafloor sediments using eXpendable Bottom Penetrometer, she collaborated with Dr. Thomas Wever from the Institute for Underwater Acoustics and Geophysics of the German Navy in Kiel. She finished her Ph.D. in Marine Geotechnics in 2011 at MARUM-Center for Marine and Environmental Sciences at the University of Bremen, Germany. She worked on the “Geotechnical investigation of sediment remobilization processes using dynamic penetrometers” under the supervision of Prof. Achim Kopf. She was a postdoctoral fellow in 2011 in the marine geotechnics group at MARUM under supervision of Prof. Achim Kopf and, from 2012-2013, in the physical oceanography group at Dalhousie University, Halifax, Canada, under the supervision of Dr. Alex Hay, before being appointed assistant professor in the geotechnical engineering group of the Department of Civil and Environmental Engineering at Virginia Tech in Fall 2013. Her research focuses on coastal and marine geotechnics including instrument development, the geotechnical investigation of subaqueous sediment dynamics, beach dynamics, offshore renewable energies and navigation channel deepening and maintenance. She developed the free-fall penetrometer “Nimrod” in the framework of her Ph.D. and collaborated with BlueCDesigns on the design of “BlueDrop.” To date she has conducted more than 50 field surveys in the North Sea, Baltic Sea, Northern Atlantic, Arctic, Northern, Central and Southern Pacific, as well as in a number of lakes and rivers.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.343
Threshold uncertainty score0.682

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0030.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.019
GPT teacher head0.203
Teacher spread0.184 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2016
Admission routes1
Has abstractyes

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